Hi, I'm @avcton Muhammad Ahmad
Building production AI systems that ship. From agentic apps to full-stack products.
About
It started earlier than most.
My journey in tech started earlier than most. I was ten when I installed my first Ubuntu, in seventh grade when I shipped my first Android app, in tenth when I built a Hackintosh just to see if I could. The tools changed. The pull didn't.
Now I build production AI at Dubizzle Labs; agentic systems, voice pipelines, and ML infra for Bayut, Zameen & OLX across the GCC.
Now
What I'm working on.
Voice AI for real-estate sales across Saudi Arabia, UAE, and Pakistan. Converting at multiples of human telesales, with tens of thousands of calls throughout multiple campaigns.
Conversion rate
~6%
Conversion lift
4-5×
Calls placed
80k+
Selected work
Things I've shipped.
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Voice AI @ Dubizzle Labs
Production Arabic calling agents that speak natively. Boardroom-grade conversion results.
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Interview Sensei
A living AI avatar that interacts & interviews you in real-time. 2× National Competitions Winner
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Genomaly
GAN/VAE anomaly detection applied to pharma quality control. 82% accuracy on capsule defects.
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Visionary GenAI
ViT for spoof detection, CLIP for text-image retrieval over 5K images, Stable Diffusion for generation. Three tasks, one pipeline.
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NS3 Docker Utility
Pre-configured NS3 network simulation environment on Docker. Adopted by an entire CS section for mid-exams; ~500 organic visitors.
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Fiscal Count
.NET ERP for a real manufacturing client. Led a team of 5 engineers. From prototype to first production system shipped.
Experience
Track.
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- Built and led production Arabic AI calling agents across 7 campaigns (peak ~80k calls); ~6% conversion rate and a 4-5x lift over the human telesales baseline.
- Directed voice cloning sessions and engineered a dialect-native Translation Layer; drove GoClaw adoption as the company-wide agentic platform after a live CEO boardroom demo.
- Built async ML pipelines for broker photo processing (OpenAI, Sidekiq, WebP), established SIP trunking with Telnyx, and deployed Dubizzle's first production n8n automation platform.
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- Built Interview Sensei end-to-end: real-time AI mock interviews with a 3D avatar, WebRTC video/audio, STT/TTS, LLM-driven question generation, and post-session analytics.
- Deployed on Nextbridge's RTX 4090 via NGINX reverse proxy with GPU session rate-limiting for concurrent interview sessions.
- 1st at FAST Job Fair 2025 (250+ FYPs; first-ever DS team to win) and 1st at SOFTEC 2025 SPC.
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- Built a Flutter mobile app with custom theming, routing, and session management; backed by a Dockerized Node.js/Express + MongoDB service.
- Optimized DB query execution by 30% via Mongoose ORM; delivered 20+ API endpoints across 10+ sprint cycles over an 8-month remote engagement.
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- Engineered a PHP CodeIgniter data model processing 50,000+ airline ticket records monthly; improved data handling efficiency by 30%.
- Automated XML airline data parsing into target schema; cut manual processing time by ~40% at ~99% accuracy.
Stack & Tools
What I build with.
Education
School.
FYP: Interview Sensei. First DS team to win Job Fair + SOFTEC SPC 2025.
Recognition
Receipts.
Voices
In their words.
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Rare combination of research depth and practical engineering. Interview Sensei was ready to ship the day we judged it.
Amir Quddus Industry Judge SOFTEC 2025 -
One of the sharpest students I've taught. His final project won two national competitions; the engineering quality was production-ready from day one.
Anonymous Professor Faculty FAST NUCES
Digital Garden
What I've been thinking about.
Notes, essays, half-finished thoughts. Tended in public.
How We'd Work Together
Got something we can build? Here's the journey.
From first conversation to a working system in production. Five steps · ~6 weeks to v1.
- 01 INTRO
First conversation
A 30-minute call to understand the problem, the constraints, and whether an AI system is actually the right shape for it.
30-min intro call - 02 SCOPE
Define the problem space
I map the domain: data sources, edge cases, evaluation criteria. What does a good outcome look like from your users' perspective?
Scope doc · data audit - 03 BUILD
Working prototype
First end-to-end system: model, pipeline, interface. Something you can interact with, demo, and break. Usually two weeks to v0.1.
v0.1 – live and testable - 04 EVAL
Eval and iterate
Benchmarks, failure modes, human evaluation. Numbers honest enough to present to a board. Iterate until the system earns its place.
Benchmark report - 05 SHIP
Production rollout
Integrated with your stack, monitored, documented. The system runs reliably without me watching it.
v1.0 → deployed
Contact
Email is best. I read everything. I reply to most things.
Message received.
Thanks for reaching out. I usually reply within 4-6 hours.